hypervolume 
Niches of the species are compared using Hutchinson's multidimensional hypervolume as a model.


Its underlying core data structure is a novel 4D spatiotemporal representation which we call the video hypervolume.


In this paper we present a method to estimate the noise distance in noise clustering based on the preservation of the hypervolume of the feature space.


A fivedimensional hypervolume constituted the experimental design space.


Any comprehensive investigation of a multivariate endocrine system should also include an analysis of variance (σ), as it may provide additional insights into the dynamics of an endocrine hypervolume.


A minimization of the fuzzy hypervolume makes no sense here.


Also in all problems, as the number of spheres increases the models require more and more evaluations to reach the predefined hypervolume level.


As with any probability density function, this function is positive and the hypervolume under the curve equals one.


At the limit of a single nearest neighbor, the decision boundary is a hypervolume around each point.


For example, GathGeva's index that uses the value of fuzzy hypervolume as a measure is a good choice for compact clusters.


Furthermore, as dimension increases, exponentially more domain points are required to maintain a constant number of points per unit hypervolume.


For the closeness of the obtained POF, we use the hypervolume H.


For example, a single random hyperplane would create rather trivial clustering of ddimensional data by cutting the hypervolume into two regions.


From the obtained hypervolume can be concluded that the distribution properties can be slightly improved by the supporting use of VADS.


For three objectives, the variants of MSOPS using 50 target vectors obtain the maximal hypervolume among the aggregation methods.


For example, the S metric of Zitzler and Thiele48 calculates the hypervolume of the kdimensional region covered by the approximation set.


However, there exists no compatible and complete or compatible and complete comparison method solely based on the binary hypervolume indicator.


Optimalnumber of substructures in the data set can be estimated from the minimum of the fuzzy hypervolume and maximum of partition density.


Optimal number of substructures in the data set can be estimated from the minimum of the fuzzy hypervolume and maximum of partition density.


So the first step is to estimate the hypervolume of the feature space.

